A general and computationally inexpensive algorithmic scheme is presented that falls in a region detection category. In the scheme, a minimal spanning tree is used as a path of a sequential region grower. The algorith...
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A general and computationally inexpensive algorithmic scheme is presented that falls in a region detection category. In the scheme, a minimal spanning tree is used as a path of a sequential region grower. The algorithm traverses the spatially adjacent graph while maintaining the structural organization of an image. The graph-theoretical evaluation of heuristics is described and examples of implementation are given.
A computer software package called NETWRK is presented. This software package consists of a set of program modules for automatic analysis and interpretation of stereological parameters characterizing lung tissue micro...
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A computer software package called NETWRK is presented. This software package consists of a set of program modules for automatic analysis and interpretation of stereological parameters characterizing lung tissue micrographs. The modules are linked using a table-driven control driver. By altering table parameters, different process architectures are effected. The major tasks performed by this software package are optimal threshold determination, total intercept counting, object profile skeleton generation, and determination of primary parameters. This project served as a test study in examining the effects of applying modularity, levels of abstraction, and other software engineering techniques to imageprocessing architecture and software In particular, the adaptability, modifiability, maintainability, and efficiency of the generated software is examined.
A system is described that detects object outlines in television images in real-time. A high-speed pipeline processor transforms the raw image into an edge map and a microprocessor, which is integrated into the system...
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A system is described that detects object outlines in television images in real-time. A high-speed pipeline processor transforms the raw image into an edge map and a microprocessor, which is integrated into the system, clusters the edges and represents them as chain codes. image statistics, useful for higher level tasks such as patternrecognition, are computed by the microprocessor. Peak intensity and peak gradient values are extracted within a programmable window and are used for iris and focus control. The algorithms implemented in hardware and the pipeline processor architecture are described. The strategy for partitioning functions in the pipeline was chosen to make the implementation modular. The microprocessor interface allows flexible and adaptive control of the feature extraction process.
This conference proceedings contains 156 papers, of which 3 are given in abstract form only;145 papers are indexed separately. The topics covered are: software development methodology;storage structure and file design...
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This conference proceedings contains 156 papers, of which 3 are given in abstract form only;145 papers are indexed separately. The topics covered are: software development methodology;storage structure and file design;patternrecognition software;telecommunications software;computer-aided circuit design;software requirements and specifications;schema and view design;data base design;manufacturing software;automatic visual inspection;diagnostic and therapeutic systems;query description and processing;robots;biomedical imageprocessing;distributed processing;software testing;computer graphics;data base management;microcomputer software;and Petri nets and other computation models.
Inference techniques are applied to computing systems to improve the allocation of resources for fault tolerant performance. Using a general model for such systems, the influence of estimation errors for system parame...
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Inference techniques are applied to computing systems to improve the allocation of resources for fault tolerant performance. Using a general model for such systems, the influence of estimation errors for system parameters on the resulting system fault performance is examined. These results are then applied to the problem of error mode testing-finding the underlying error structure of the system. Simulation is used to illustrate the properties discussed.
A theory is proposed for the structure of edges in a two dimensional visual field. This theory consists of models of ideal edges, and of distortion criteria for the evaluation of the accuracy with which a visual field...
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A theory is proposed for the structure of edges in a two dimensional visual field. This theory consists of models of ideal edges, and of distortion criteria for the evaluation of the accuracy with which a visual field fits this model. In this formulation the edge is specified by a curve described by a pair of parametric equations, and the line or edge detection problem is solved by minimizing a cost function over the set of curves.
Presented are the details of a study conducted in the general area of patternrecognition. Broadly speaking, the objective was to identify ways by which a patternrecognition system could be implemented on a microcomp...
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Presented are the details of a study conducted in the general area of patternrecognition. Broadly speaking, the objective was to identify ways by which a patternrecognition system could be implemented on a microcomputer in a feasible way through a specific design. Such a design would strive to take advantage of mathematical equivalencies by which reductions in processing complexities would be achieved and provide a test bed for design tradeoffs and sensitivity studies. Automatic Speech recognition is broken into four sequential processing stages: data acquisition, preprocessing, feature extraction and classification. A microcomputer was selected to implement an all-digital version of an automatic speech recognition system based on the technique first developed by T. B. Martin. It is constrained to a restricted vocabulary and a limited set of users.
There is presented the software implementation of a new type of region grower for object boundary finding when the boundaries are highly variable and the images very noisy. The approach is both structural and probabil...
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There is presented the software implementation of a new type of region grower for object boundary finding when the boundaries are highly variable and the images very noisy. The approach is both structural and probabilistic and consists of data modeling followed by boundary finding through statistical estimation realized as cost functional minimization. The algorithm, involving a first guess at the boundary followed by successively improving approximations, is described, and also described is its implementation and experimental results.
The algorithm presented is a direct approach to the problem of determining a linear discriminant function which minimizes total classification error in a two-class training set. Discriminant function coefficients are ...
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The algorithm presented is a direct approach to the problem of determining a linear discriminant function which minimizes total classification error in a two-class training set. Discriminant function coefficients are determined by a search technique which is based on two theorems derived from convexity theory. The number of iterative steps in the search sequence has a theoretical upper bound which is strictly less than the number required for all enumeration, and applications of the algorithm to experimental data have established its tractability under nontrivial conditions. Although the training set patterns are initially assumed to be in general position, this restriction is essentially eliminated by an extension of the algorithm which is briefly discussed.
An optimal linear discriminant function algorithm is introduced which minimizes the error rate of internal samples. It is applied to two sets of data. One data set is imaginary and the other is actual data drawn from ...
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An optimal linear discriminant function algorithm is introduced which minimizes the error rate of internal samples. It is applied to two sets of data. One data set is imaginary and the other is actual data drawn from the medical field.
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